{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "frank-quebec",
   "metadata": {},
   "source": [
    "## 1 介绍"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "patent-manor",
   "metadata": {},
   "outputs": [],
   "source": [
    "## 2 模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fifty-zealand",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "def evalModel():\n",
    "    model = solution('eval')\n",
    "    ad_data = model.readData()\n",
    "    ad_data = model.convert_data(ad_data)\n",
    "    data, target = model.datafilter(ad_data)\n",
    "    # model.writeFeature(data)\n",
    "    # model.modelFiveFoldEval(data, target)\n",
    "    model.modelDayEval(data, target)\n",
    "    return data\n",
    "\n",
    "\n",
    "def train(modelChoice):\n",
    "    # train process\n",
    "    model = solution('eval')\n",
    "    ad_data = model.readData()\n",
    "    ad_data = model.convert_data(ad_data)\n",
    "    data, target = model.datafilter(ad_data)\n",
    "    model.modelTrain(data, target, modelChoice)\n",
    "\n",
    "def test(modelChoice):\n",
    "    # test process\n",
    "    model = solution('test')\n",
    "    ad_data = model.readData()\n",
    "    ad_data = model.convert_data(ad_data)\n",
    "    data = model.datafilter(ad_data)\n",
    "    preds = model.modelTest(data, modelChoice)\n",
    "    return preds\n"
   ]
  }
 ],
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